This paper presents a Bayesian probabilistic framework to assess soilproperties and model uncertainty to better predict excavation-induced deformationsusing field deformation data. The potential correlations between deformations atdifferent depths are accounted for in the likelihood function needed in the Bayesianapproach. The proposed approach also accounts for inclinometer measurement errors.The posterior statistics of the unknown soil properties and the model parameters arecomputed using the Delayed Rejection (DR) method and the Adaptive Metropolis(AM) method. As an application, the proposed framework is used to assess theunknown soil properties of multiple soil layers using deformation data at differentlocations and for incremental excavation stages. The developed approach can be usedfor the design of optimal revisions for supported excavation systems.
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